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Research Article | Open Access

PuzzleSorter: Certainty-aware visual restoration of multiple cultural artifacts

State Key Lab of CAD&CG, Zhejiang University, Hangzhou 310058, China
Laboratory of Art and Archaeology Image, Zhejiang University, Hangzhou 310058, China
School of Advanced Technology, Xi’an Jiaotong–Liverpool University, Suzhou 215123, China
School of Art and Archaeology, Zhejiang University, Hangzhou 310058, China
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Abstract

We present PuzzleSorter, a certainty-aware visual analytics system for cultural relic fragment restoration. Restoring cultural objects from broken fragments is a fundamental task in geometry and archaeology. Prior research proposes automatic models to classify fragments by types and assemble matched pairs successively. However, eroded fragments lead to erroneous results, posing two challenges for restorers to correct: (1) numerous fragments conceal errors within an overwhelming number of object appearances, and (2) the unknown difficulty of restoration hinders correction strategy development. To address these challenges, PuzzleSorter provides multi-criteria analysis that helps users identify certainties of current solutions and alternatives at the type, object, and fragment levels. Moreover, our system visualizes these certainties through a relation graph, which implies alternative assembly solutions with geometric context and indicates correction difficulties through neighbor proximity, number of neighbors, and path length. We demonstrate the feasibility and utility of our system through two case studies and expert interviews.

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Computational Visual Media
Pages 1281-1302

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Cite this article:
Ye S, Yin J, Zhou B, et al. PuzzleSorter: Certainty-aware visual restoration of multiple cultural artifacts. Computational Visual Media, 2025, 11(6): 1281-1302. https://doi.org/10.26599/CVM.2025.9450468

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Received: 26 July 2024
Accepted: 28 October 2024
Published: 12 December 2025
© The Author(s) 2025.

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